The overall objective of this project is to enhance our understanding of acute lung injury (ALI) pathogenesis and to expand the potential utility of biomarkers and metabolomic analysis. Acute lung injury (ALI) is a life- threatening disease that affects 200,000 people each year in the US and, because there is no defined medical therapy, mortality rates remain high. Our ability to determine which at-risk patients will progress to ALI i limited, and although specific biomarkers have been identified, there remain unanswered questions about how these biomarkers contribute to ALI pathogenesis. RAGE is a marker of alveolar epithelial lung injury, and elevated levels of soluble RAGE (sRAGE) have been identified in the BALF of patients with ALI when compared to non-ALI patients. However, the RAGE activation pathway is complex and there is limited data explaining the mechanism of sRAGE entry into the alveolar space. HMGGB1 and MMPs have been implicated in the RAGE pathway; however, data showing that all these markers are concomitantly increased in ALI is unavailable. Analyzing specimens from the NHLBI biologic specimen repository allows us to confirm and extend our initial observations about sRAGE and active metabolite patterns. We propose to test the hypothesis that sRAGE, HMGB1 and MMP-3 and -13 work as a functioning unit and changes in levels over time in ALI patients will be associated with mortality. We will extend this data using metabolomics to show that specific metabolic pathways are associated with biomarker activation and survival status. The specific aims are designed to : 1) test the hypothesis that sRAGE, HMGB1 and MMPs are coordinately increased in the BALF of patients with ALI compared to controls at risk for ALI; and determine whether sustained increases in sRAGE, HMGB1 and MMP levels over time are associated with mortality in ALI patients; and 2) develop a high- resolution metabolomic database for ALI linked to outcomes in order to: determine the association between specific metabolomic pathways and biomarkers analyzed in Aim 1, and identify candidate metabolites that differentiate ALI survivors and non-survivors. To test our hypotheses we will analyze BAL samples from the NHLBI biorepository obtained from the ARDSnet LaSRS trial, which provides BALF collected at two different time points. As a control population, we will also obtain BALF from mechanically ventilated patients with an at- risk diagnosis for ALI. We will perform assays measuring HMGB1, MMP-3 and -13, and sRAGE both in BALF. Metabolomic profiling of ARDS patients will be performed via high-resolution mass spectrometry. The long- term goal is to develop an affordable approach that can be used for predicting disease susceptibility, diagnosis, risk stratification, response to therapy and prognosis.